Information Processing Letters
Principles of database and knowledge-base systems, Vol. I
Principles of database and knowledge-base systems, Vol. I
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Inferring decision trees using the minimum description length principle
Information and Computation
Elements of information theory
Elements of information theory
C4.5: programs for machine learning
C4.5: programs for machine learning
Learning Boolean concepts in the presence of many irrelevant features
Artificial Intelligence
Estimating attributes: analysis and extensions of RELIEF
ECML-94 Proceedings of the European conference on machine learning on Machine Learning
Creating abstractions using relevance reasoning
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Uncertainly measures of rough set prediction
Artificial Intelligence
Feature Selection via Discretization
IEEE Transactions on Knowledge and Data Engineering
Occam Algorithms for Computing Visual Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of the 2001 ACM symposium on Applied computing
Convergence and Application of Online Active Sampling Using Orthogonal Pillar Vectors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Maximally informative k-itemsets and their efficient discovery
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
A parameterless feature ranking algorithm based on MI
Neurocomputing
Feature Selection via Maximizing Neighborhood Soft Margin
ACML '09 Proceedings of the 1st Asian Conference on Machine Learning: Advances in Machine Learning
Selecting discrete and continuous features based on neighborhood decision error minimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Effective feature selection scheme using mutual information
Neurocomputing
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
An effective feature selection scheme via genetic algorithm using mutual information
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
ACSC '11 Proceedings of the Thirty-Fourth Australasian Computer Science Conference - Volume 113
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Relevance has traditionally been linked with feature subset selection, but formalization of this link has not been attempted. In this paper, we propose two axioms for feature subset selection驴sufficiency axiom and necessity axiom驴based on which this link is formalized: The expected feature subset is the one which maximizes relevance. Finding the expected feature subset turns out to be NP-hard. We then devise a heuristic algorithm to find the expected subset which has a polynomial time complexity. The experimental results show that the algorithm finds good enough subset of features which, when presented to C4.5, results in better prediction accuracy.